Policy Uses of Federal Statistics

1. Policy Uses of Federal Statistics Rebecca M. Blank Department of Commerce

2. Data provides information about us as a society from which we can tell stories about how our world and our lives are changing

3. Chart: Age and Gender Distribution of U.S. Population: 1970, 1990, 2008 A. 1970 B. 1990 Male Female Percent Percent C. 2008 Source: Statistical Abstract of the United States,1996, Tables 14 & 47. Statistical Abstract of the United States,1992, Table 40. U.S. Census Bureau, Table 1: Annual Estimates of the Resident Population by Sex and Five-Year Age Groups for the United States: April 1, 2000 to July 1, 2008 (NC-EST2008-01)

4. Official Statistics Statistics imbedded in tradition and law, produced and released by a data agency of the government • Concept is important to policymakers • Have a consistent definition over time (although it may be updated/improved) • Often drive data collection efforts

5. 1. How Do Official Statistics Originate? Combination of • Private analysis • Public analysis • Legislative push • Executive push

6. Examples of origin stories • National Income and Product Accounts • Unemployment rates In each case: • Data developed by researchers • Legislative & administrative interest • Formal definition provided within data agency

7. Contrasting example: Poverty Measurement 1963 calculation, requested by WH Poverty threshold= 3 * food budget (based on 1955 Household expenditure data) Family resource definition: Cash income Updated since then with price adjustments to the threshold.

9. Contrasting example: Poverty Measurement The result? Changing and updating the poverty measure has been impossible. Any change must be approved within the White House…and no president has an incentive to announce major changes in the poverty statistic.

10. 2. Official Statistics Require Judgment No statistic is a ‘simple statistic’

11. Marriage Example Percent married: But what’s the definition of marriage? • Legally sanctioned by the state? • Religiously sanctioned? • Self-declared?

12. Marriage Example This is a significant issue for Census data around same-sex marriage Numbers show a much larger number than is credible. • Is this self-reporting relative to legal marriage? • Does this reflect reporting errors? What should our official count of ‘percent married’ be reporting?

13. Poverty Example Poverty measurement requires a poverty threshold and a resource definition. Poverty threshold: could be based on • Expenditure shares • Percent of median income • Bottom –up budget calculation • Self-reports

14. Chart: Alternate Poverty Measures in Current Dollars, 1947-2007 (for a family of four) Data Sources: Gallup data from Jones (2007) and Vaughan (1993). Poverty thresholds and median income levels from U.S. Census Bureau historical tables. Notes: Gallup polls ask about the minimum amount of money a family of four would need to "get along in your local community." Gallup estimates are response means, except for 1967, 1987, and 2007, which are medians. Mean and median Gallup responses track together closely across the years for which both numbers are available. 50 percent median income figures and poverty thresholds are for a family of four.

15. Poverty Example Equally complex: What resources do you count? • Cash • After tax? • In-Kind? Including health care? Do you adjust for cost of living differences between areas?

16. 3. Alternative Numbers Can Help Interpret Official Statistics...Sometimes Statistics are always better interpreted when placed in context…in comparison to history, to other countries, or to other closely-related statistics Useful examples: • Alternative Unemployment measures • Satellite GDP accounts

17. Chart: Unemployment Rate - Alternative Measures Source: U.S. Bureau of Labor Statistics, Table A-12: Alternative Measures of Labor Underutilization, www.bls.gov/webapps/legacy/cpsatab12.htm

18. Not useful examples Alternative measures of health insurance coverage Uninsured________ SurveyYearfor full year@time of survey CPS 2007 45.7 m N/A (15.3%) MEPS 2006 37.1 m 47.3 m (14.5%) (16.6%) NHIS 2007 30.6 m 43.1 m (10.3%) (14.5%) SIPP 2001 18.9 m 38.7 m (6.8%) (14.0%)

19. Alternatives need to be coherent Most useful when they vary along an understandable dimension: • Different definitions within the same data; or • Same definitions but measured in different populations or surveys.

20. 4. Official Statistics are Different from Program Eligibility Criteria Most statistics are aggregate, telling us something about the group But programs need individual eligibility information

21. Poverty measurement has been used for both purposes • This has limited the ability to developed a more nuanced poverty measure • Makes changes almost impossible to contemplate

22. Conclusions The process by which official statistics are created matters. It’s particularly important to leave their definition and updating to a data agency over time; don’t try to set it in law or regulation. (Of course, for credibility, the release of official statistics also belongs in the data agency.)

23. Conclusions All definitions require some degree of judgment. Nothing wrong with responding to political and public debate on these issues. Indeed, that debate typically reflects valid concerns about existing statistics.

24. Conclusions Sometimes two statistics (or more) are better than one. These should not be arbitrary ‘add-ons’ but developed as part of a coherent data strategy.

25. Conclusions Statistics are developed to tell us something about aggregate well-being. This may not be appropriately used to determine individual well-being.

26. Thank you!